mirror of
https://github.com/ClickHouse/ClickHouse.git
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350 lines
9.1 KiB
C++
350 lines
9.1 KiB
C++
#pragma once
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#include <city.h>
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#include <type_traits>
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#include <stats/UniquesHashSet.h>
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#include <DB/IO/WriteHelpers.h>
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#include <DB/IO/ReadHelpers.h>
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#include <DB/IO/WriteBufferFromString.h>
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#include <DB/DataTypes/DataTypesNumberFixed.h>
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#include <DB/DataTypes/DataTypeString.h>
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#include <DB/Interpreters/AggregationCommon.h>
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#include <DB/Common/HashTable/HashSet.h>
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#include <DB/Common/HyperLogLogWithSmallSetOptimization.h>
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#include <DB/Common/CombinedCardinalityEstimator.h>
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#include <DB/Columns/ColumnString.h>
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#include <DB/AggregateFunctions/IUnaryAggregateFunction.h>
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#include <DB/AggregateFunctions/UniqCombinedBiasData.h>
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namespace DB
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{
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/// uniq
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struct AggregateFunctionUniqUniquesHashSetData
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{
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typedef UniquesHashSet<DefaultHash<UInt64> > Set;
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Set set;
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static String getName() { return "uniq"; }
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};
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/// uniqHLL12
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template <typename T>
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struct AggregateFunctionUniqHLL12Data
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{
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typedef HyperLogLogWithSmallSetOptimization<T, 16, 12> Set;
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Set set;
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static String getName() { return "uniqHLL12"; }
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};
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template <>
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struct AggregateFunctionUniqHLL12Data<String>
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{
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typedef HyperLogLogWithSmallSetOptimization<UInt64, 16, 12> Set;
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Set set;
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static String getName() { return "uniqHLL12"; }
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};
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/// uniqExact
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template <typename T>
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struct AggregateFunctionUniqExactData
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{
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typedef T Key;
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/// При создании, хэш-таблица должна быть небольшой.
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typedef HashSet<
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Key,
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DefaultHash<Key>,
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HashTableGrower<4>,
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HashTableAllocatorWithStackMemory<sizeof(Key) * (1 << 4)>
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> Set;
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Set set;
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static String getName() { return "uniqExact"; }
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};
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/// Для строк будем класть в хэш-таблицу значения SipHash-а (128 бит).
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template <>
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struct AggregateFunctionUniqExactData<String>
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{
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typedef UInt128 Key;
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/// При создании, хэш-таблица должна быть небольшой.
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typedef HashSet<
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Key,
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UInt128TrivialHash,
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HashTableGrower<3>,
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HashTableAllocatorWithStackMemory<sizeof(Key) * (1 << 3)>
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> Set;
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Set set;
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static String getName() { return "uniqExact"; }
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};
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template <typename T, HyperLogLogMode mode>
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struct BaseUniqCombinedData
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{
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using Key = UInt32;
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using Set = CombinedCardinalityEstimator<
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Key,
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HashSet<Key, TrivialHash, HashTableGrower<> >,
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16,
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14,
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17,
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TrivialHash,
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UInt32,
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HyperLogLogBiasEstimator<UniqCombinedBiasData>,
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mode
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>;
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Set set;
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};
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template <HyperLogLogMode mode>
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struct BaseUniqCombinedData<String, mode>
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{
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using Key = UInt64;
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using Set = CombinedCardinalityEstimator<
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Key,
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HashSet<Key, TrivialHash, HashTableGrower<> >,
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16,
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14,
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17,
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TrivialHash,
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UInt64,
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HyperLogLogBiasEstimator<UniqCombinedBiasData>,
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mode
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>;
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Set set;
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};
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/// Агрегатные функции uniqCombinedRaw, uniqCombinedLinearCounting, и uniqCombinedBiasCorrected
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/// предназначены для разработки новых версий функции uniqCombined.
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/// Пользователи должны использовать только uniqCombined.
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template <typename T>
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struct AggregateFunctionUniqCombinedRawData
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: public BaseUniqCombinedData<T, HyperLogLogMode::Raw>
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{
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static String getName() { return "uniqCombinedRaw"; }
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};
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template <typename T>
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struct AggregateFunctionUniqCombinedLinearCountingData
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: public BaseUniqCombinedData<T, HyperLogLogMode::LinearCounting>
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{
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static String getName() { return "uniqCombinedLinearCounting"; }
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};
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template <typename T>
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struct AggregateFunctionUniqCombinedBiasCorrectedData
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: public BaseUniqCombinedData<T, HyperLogLogMode::BiasCorrected>
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{
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static String getName() { return "uniqCombinedBiasCorrected"; }
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};
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template <typename T>
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struct AggregateFunctionUniqCombinedData
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: public BaseUniqCombinedData<T, HyperLogLogMode::FullFeatured>
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{
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static String getName() { return "uniqCombined"; }
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};
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namespace detail
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{
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/** Хэш-функция для uniq.
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*/
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template <typename T> struct AggregateFunctionUniqTraits
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{
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static UInt64 hash(T x) { return x; }
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};
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template <> struct AggregateFunctionUniqTraits<Float32>
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{
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static UInt64 hash(Float32 x)
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{
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UInt64 res = 0;
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memcpy(reinterpret_cast<char *>(&res), reinterpret_cast<char *>(&x), sizeof(x));
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return res;
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}
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};
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template <> struct AggregateFunctionUniqTraits<Float64>
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{
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static UInt64 hash(Float64 x)
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{
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UInt64 res = 0;
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memcpy(reinterpret_cast<char *>(&res), reinterpret_cast<char *>(&x), sizeof(x));
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return res;
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}
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};
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/** Хэш-функция для uniqCombined.
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*/
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template <typename T> struct AggregateFunctionUniqCombinedTraits
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{
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static UInt32 hash(T x) { return static_cast<UInt32>(intHash64(x)); }
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};
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template <> struct AggregateFunctionUniqCombinedTraits<Float32>
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{
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static UInt32 hash(Float32 x)
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{
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UInt64 res = 0;
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memcpy(reinterpret_cast<char *>(&res), reinterpret_cast<char *>(&x), sizeof(x));
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return static_cast<UInt32>(intHash64(res));
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}
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};
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template <> struct AggregateFunctionUniqCombinedTraits<Float64>
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{
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static UInt32 hash(Float64 x)
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{
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UInt64 res = 0;
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memcpy(reinterpret_cast<char *>(&res), reinterpret_cast<char *>(&x), sizeof(x));
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return static_cast<UInt32>(intHash64(res));
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}
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};
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/** Структура для делегации работы по добавлению одного элемента в агрегатные функции uniq.
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* Используется для частичной специализации для добавления строк.
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*/
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template <typename T, typename Data, typename Enable = void>
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struct OneAdder;
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template <typename T, typename Data>
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struct OneAdder<T, Data, typename std::enable_if<
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std::is_same<Data, AggregateFunctionUniqUniquesHashSetData>::value ||
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std::is_same<Data, AggregateFunctionUniqHLL12Data<T> >::value>::type>
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{
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template <typename T2 = T>
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static void addOne(Data & data, const IColumn & column, size_t row_num,
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typename std::enable_if<!std::is_same<T2, String>::value>::type * = nullptr)
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{
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const auto & value = static_cast<const ColumnVector<T2> &>(column).getData()[row_num];
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data.set.insert(AggregateFunctionUniqTraits<T2>::hash(value));
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}
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template <typename T2 = T>
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static void addOne(Data & data, const IColumn & column, size_t row_num,
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typename std::enable_if<std::is_same<T2, String>::value>::type * = nullptr)
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{
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StringRef value = column.getDataAt(row_num);
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data.set.insert(CityHash64(value.data, value.size));
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}
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};
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template <typename T, typename Data>
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struct OneAdder<T, Data, typename std::enable_if<
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std::is_same<Data, AggregateFunctionUniqCombinedRawData<T> >::value ||
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std::is_same<Data, AggregateFunctionUniqCombinedLinearCountingData<T> >::value ||
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std::is_same<Data, AggregateFunctionUniqCombinedBiasCorrectedData<T> >::value ||
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std::is_same<Data, AggregateFunctionUniqCombinedData<T> >::value>::type>
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{
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template <typename T2 = T>
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static void addOne(Data & data, const IColumn & column, size_t row_num,
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typename std::enable_if<!std::is_same<T2, String>::value>::type * = nullptr)
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{
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const auto & value = static_cast<const ColumnVector<T2> &>(column).getData()[row_num];
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data.set.insert(AggregateFunctionUniqCombinedTraits<T2>::hash(value));
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}
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template <typename T2 = T>
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static void addOne(Data & data, const IColumn & column, size_t row_num,
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typename std::enable_if<std::is_same<T2, String>::value>::type * = nullptr)
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{
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StringRef value = column.getDataAt(row_num);
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data.set.insert(CityHash64(value.data, value.size));
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}
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};
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template <typename T, typename Data>
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struct OneAdder<T, Data, typename std::enable_if<
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std::is_same<Data, AggregateFunctionUniqExactData<T> >::value>::type>
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{
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template <typename T2 = T>
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static void addOne(Data & data, const IColumn & column, size_t row_num,
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typename std::enable_if<!std::is_same<T2, String>::value>::type * = nullptr)
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{
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data.set.insert(static_cast<const ColumnVector<T2> &>(column).getData()[row_num]);
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}
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template <typename T2 = T>
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static void addOne(Data & data, const IColumn & column, size_t row_num,
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typename std::enable_if<std::is_same<T2, String>::value>::type * = nullptr)
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{
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StringRef value = column.getDataAt(row_num);
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UInt128 key;
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SipHash hash;
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hash.update(value.data, value.size);
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hash.get128(key.first, key.second);
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data.set.insert(key);
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}
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};
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}
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/// Приближённо вычисляет количество различных значений.
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template <typename T, typename Data>
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class AggregateFunctionUniq final : public IUnaryAggregateFunction<Data, AggregateFunctionUniq<T, Data> >
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{
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public:
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String getName() const { return Data::getName(); }
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DataTypePtr getReturnType() const
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{
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return new DataTypeUInt64;
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}
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void setArgument(const DataTypePtr & argument)
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{
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}
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void addOne(AggregateDataPtr place, const IColumn & column, size_t row_num) const
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{
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detail::OneAdder<T, Data>::addOne(this->data(place), column, row_num);
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}
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void merge(AggregateDataPtr place, ConstAggregateDataPtr rhs) const
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{
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this->data(place).set.merge(this->data(rhs).set);
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}
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void serialize(ConstAggregateDataPtr place, WriteBuffer & buf) const
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{
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this->data(place).set.write(buf);
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}
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void deserializeMerge(AggregateDataPtr place, ReadBuffer & buf) const
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{
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this->data(place).set.readAndMerge(buf);
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}
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void insertResultInto(ConstAggregateDataPtr place, IColumn & to) const
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{
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static_cast<ColumnUInt64 &>(to).getData().push_back(this->data(place).set.size());
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}
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};
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}
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